Biomedical signals and Artificial Intelligence Towards Smart Robots Control Strategies

Navigation is a critical aspect for mobile robots, involving the determination or estimation of the robot's position, velocity, and attitude. It is closely associated with feedback control, which focuses on designing systems to govern the robot's movement. Over the years, numerous control methods have been developed, each with its own set of advantages and disadvantages when compared to other methods. These methods can be broadly categorized into two groups: Classical Control and Intelligent Control. The categorization is based on the distinctive benefits offered by each approach. Control encompasses the manipulation of actuators to execute guidance commands and maintain vehicle stability. Recent advancements in the field focus on determining and controlling the various states of the vehicle, such as position, direction, attitude, altitude, velocity, among others. Intelligent handling of dangerous situations, such as collisions and adverse environmental conditions like temperature, radiation, and weather, is essential for the successful operation of robots.

This special session focuses on the integration of biomedical signals (e.g., EEG, EMG) and artificial intelligence in the development of control strategies for smart robots, particularly in terms of smart tracking control and navigation. When tracking a trajectory, robots often encounter obstacles that can pose a threat to the robot, impede navigation, or alter the desired trajectory. The use of biomedical signals and artificial intelligence has emerged as an exciting approach to address these challenges. The objective is to implement artificial intelligence controllers to enable optimal navigation, minimizing errors and reducing time consumption. Additionally, this Research Topic aims to discuss the imposition of predefined trajectories that mobile robots must be capable of following. We welcome original articles that present novel developments in artificial intelligence-based indoor/outdoor navigation and control strategies. The main focus is to summarize both theoretical and experimental results in this field and showcase various applications.

Possible topics for submission include:
• Integration of biomedical signals for smart robots
• Artificial intelligence control in robotics
• Path planning and self-localization / SLAM
• Path tracking, and obstacle avoidance control
• Trajectory optimization in blind and non-blind navigation
• Machine learning for robot state estimation and control
• Applications of artificial intelligence in aerial, marine, and terrestrial robot navigation and control systems
• Multi-robot / swarm system applications with artificial intelligence
• Bio-Inspired robots
• Exoskeleton robots